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Artificial intelligence and machine learning in pharmaceutical research and healthcare: Ethical challenges and a framework for responsible implementation

Background Artificial intelligence (AI) and machine learning (ML) are transforming pharmaceutical research and healthcare by enabling analysis of large-scale biomedical data and supporting data-driven decision-making. However, their rapid integration has introduced significant ethical, governance, and implementation challenges that remain insufficiently synthesized within a unified framework. Objective This work aims to synthesize the central ethical challenges and paradoxes associated with AI and ML in pharmace…

Journal of the American Pharmacists Association · Health

Artificial intelligence and machine learning in pharmaceutical research and healthcare: Ethical challenges and a framework for responsible implementation

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Research and application of machine learning models based on multimodal big data for precise transfusion management in acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a highly heterogeneous haematologic malignancy in which transfusion support represents an essential component of comprehensive patient care. This review aims to provide an updated synthesis of recent progress in the development and clinical application of machine learning models based on multimodal big data for precision transfusion management in AML, addressing the persistent limitations of conventional, empirically guided transfusion practices. We systematically reviewed the li…

Health

Evidence-backed gain

Beyond Thresholds: Can Machine Learning Improve Trauma Field Triage?

BackgroundAccurate triage of trauma patients by Emergency Medical Services (EMS) is essential for optimal outcomes and resource allocation. The 2021 National Field Triage Guidelines (FTG) assist EMS in prehospital triage; however, its collective performance has never been evaluated using a national database. We aimed to evaluate an FTG surrogate and develop a predictive model to identify patients at risk for serious injury.MethodsThe Trauma Quality Improvement Program National Trauma Databank (2017-2020) was que…

Health

Evidence-backed gain

AI-based clinician decision support system for diagnosis of inherited retinal diseases: a multicenter, randomized trial

The accurate and timely diagnosis of inherited retinal diseases (IRDs) represents an unmet clinical need in ophthalmology, as the current pathways rely on resource-intensive phenotyping, multidisciplinary expertise and genetic testing. Here we developed Retina4IRD, an artificial intelligence (AI)-based clinician decision support system (CDSS) that predicts 17 genotype categories from retina images. Retina4IRD uses a Vision Transformer model pretrained with RETFound. We then trained and validated Retina4IRD using…

Health

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Machine Learning Prediction of Hoehn and Yahr Scores at 5-Years Post-<sup>123</sup>I-Ioflupane SPECT Imaging in a Real-World Parkinson's Disease Dataset

Background Parkinson's disease (PD) progression is highly heterogeneous, complicating clinical management and prognostication. While machine learning models have been developed using research datasets such as Parkinson's Precision Medicine Initiative (PPMI) and Parkinson's Disease Biomarkers Program (PDBP), their clinical translatability is limited due to differences in routinely collected data. The Hoehn and Yahr (H&Y) scale is commonly used in clinical practice to stage PD, yet most predictive models focus on…

Health

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Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education

Abstract The present discussion examines the transformative impact of Artificial Intelligence (AI) in educational settings, focusing on the necessity for AI literacy, prompt engineering proficiency, and enhanced critical thinking skills. The introduction of AI into education marks a significant departure from conventional teaching methods, offering personalized learning and support for diverse educational requirements, including students with special needs. However, this integration presents challenges, includin…

Education

Evidence-backed gain

Early Identification of Recovery Potential After Acute Brain Injury Using Functional Near-Infrared Spectroscopy

Background Accurate early prognostication in patients with acute brain injury remains a major challenge in neurocritical care. Conventional bedside assessments provide limited insight into long-term outcomes and may not fully capture preserved brain function that supports recovery. Functional neuroimaging can detect brain activity not evident at the bedside, but its use in intensive care remains constrained by cost, logistics, and the need for stronger evidence supporting its value. Functional near-infrared spec…

Health

Treatment-Effect-Based Versus Risk-Based Targeting of Care Management Outreach in Medicaid: A Retrospective Cohort Study with Machine Learning

Medicaid care-management programs typically allocate scarce outreach capacity to beneficiaries with the highest predicted risk of an acute event, assuming that risk and responsiveness are aligned and stable across short intervals. The authors tested whether targeting outreach by predicted individualized treatment effect-the conditional average treatment effect (CATE) recomputed each calendar month-outperforms risk-based targeting. The authors analyzed 164,063 adult Medicaid beneficiaries (2,670,806 person-months…

Health

Multispecialty Dental EMRs from Chairside Audio: An Exploratory Study

The objective of this study was to develop and internally evaluate a modular large language model (LLM) system for generating standardized electronic medical records (EMRs) from dental chairside consultations under conditions of acoustic interference and specialty-specific heterogeneity. We built a controllable pipeline integrating multistage audio enhancement and local automatic speech recognition with a cascaded LLM generator. A baseline end-to-end system (system 1) was compared with an evidence-enhanced syste…

Health

Multispecialty Dental EMRs from Chairside Audio: An Exploratory Study

Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder Cancer

Background: Bladder cancer (BLCA) exhibits marked heterogeneity, and current classifiers provide limited guidance for prognosis or treatment. Because epigenetic reprogramming and metabolic rewiring jointly shape BLCA biology, we sought to identify epigenomically informed biomarkers with functional relevance. Methods: Epigenome (genome-wide promoter DNA methylation) and matched transcriptome (RNA sequencing) profiles from tumor and adjacent normal samples were integrated to identify genes with concordant differen…

Health

Google Flow Music Spaces is becoming an all-in-one AI music studio

Google has rolled out a major update for Flow Music Spaces, adding AI-powered song editing, stem splitting, image generation, lyrics, and video creation to its collaborative workspaces.

Media & Arts

Google Flow Music Spaces is becoming an all-in-one AI music studio

The Telltale Signs of an AI-Generated Song

More than half of the tracks uploaded to Deezer each day are now AI-generated, roughly 90,000 songs, which means the question of how to spot a synthetic track has moved from curiosity to job requirement for anyone handling music.

Media & Arts

The Telltale Signs of an AI-Generated Song

Guillermo Del Toro says ‘absolutely no goddamn AI’ was used in the Pan’s Labyrinth remaster.

During a Comic-Con panel about the film’s return to theaters, the director reiterated his hatred of all things AI, telling the crowd: > “What we’re protecting is the beauty and the redeeming power of art. It’s not about who gets the job. We are protecting a lineage of art. If we cut a generation of people from learning their craft, you’re cutting the rest of the history of that medium away from them for what? … I chose good. You have to put in time. You have to do every element by hand. A human made a decision o…

Media & Arts

Guillermo Del Toro says ‘absolutely no goddamn AI’ was used in the Pan’s Labyrinth remaster.

The AI jobs apocalypse probably isn’t coming anytime soon

In March, Anthropic, the cutting-edge artificial intelligence business that gave us the chatbot Claude, published an analysis on the impact of AI on employment, to help us assess the claim that intelligent robots were about to redefine human existence, ending demand for human labor. Last year in May, Anthropic’s co-founder, Dario Amodei, claimed AI could wipe out half of all entry-level jobs in one to five years. Last January, he told us AI would probably become a “general labor substitute for humans”. In June h…

Labor

The AI jobs apocalypse probably isn’t coming anytime soon

Ultra-widefield color fundus images and artificial intelligence for diagnosis of diabetic retinopathy: A systematic review and meta-analysis

Ultra-widefield (UWF) fundus cameras capture a larger retinal area without pupil dilation. We summarized evidence and diagnostic performance of artificial intelligence (AI)-driven diabetic retinopathy (DR) assessments using UWF images (UWFIs). We searched PubMed, Scopus, the Cochrane Library, and Web of Science to February 9, 2025, for studies evaluating DR using UWFIs and AI analyses. We followed the PRISMA guidelines and assessed study quality using the Joanna Briggs Institute Critical Appraisal Checklist for…

Health